High content screening (i.e., automated microscopy and image analysis) is a powerful tool for drug discovery, diagnostics, and biomedical research. Automated measurement of temporal and spatial information about targeted cellular processes can help elucidate important cellular information. For instance, such information can provide important data regarding drug-target interactions in vitro. Another example is the identification of the presence of rare abnormal cells (e.g., metastatic cancer cells) in a tissue or blood. High content screening also offers the potential to enable high-throughput experimentation.
Bulk measurement tools such as plate readers or Western blots have been used in obtaining cellular information but these tools often provide misleading averages of populations and mask behaviors of rare abnormal cells or subpopulations. Microscopy techniques, in contrast, are compatible with living cells, and working with biomolecules in their cellular microenvironment provides more accurate information about individual cell function and molecular mechanisms. Unfortunately, the throughput of manual single-cell microscopy measurements is low. Automation can increase the quantity of measurements and enhance reproducibility by limiting user bias. Current approaches to automation through robotics (used for high content screening) have, however, been cost prohibitive and remain out of reach for point-of-care diagnostics, personalized medicine, and academic use. Further, the number of independent parameters that can be measured with these tools can be limited by overlap of fluorescence spectra.
Immunophenotyping, for example identifying T-cell subpopulations, stemness, or circulating cancer cells, often requires the identification of multiple biochemical parameters. Moreover, dynamic processes such as drug permeability through a cell monolayer may be best characterized by a temporal parameter.
While there is much effort toward expanding the capabilities of the scanning optical microscopes and other currently used cytometric methods, such as flow cytometry, several other tools and techniques are being developed which aim to bring down cost and expand access through miniaturization and simplification. For instance, high-throughput, parallel fluorescence detection has been achieved by an integrated zone-plate array. See Schonbrun et al., High-throughput fluorescence detection using an integrated zone-plate array, Lab Chip, 10, 852-856 (2010). As another example, fiber-optic array scanning technology has been developed that can scan substrates 500 times faster than conventional scanning microscopy. See Hsieh et al., High speed detection of circulating tumor cells, Biosensors and Bioelectronics, 21 1893-99 (2006). Yet another alternative to mechanical scanning lens-based systems that has been developed is the wide field-of-view lens-free fluorescent imaging of micro-objects or labeled cells. See Coskun et al., Wide field-of-view lens-free fluorescent imaging on a chip, Lab Chip, 10, 824-827 (2010). This compact technology has achieved ˜10 μm spatial resolution over an 8-cm2 field-of-view with a single image. While some of these techniques are well equipped to identify rare, single-cell events, however, positive and negative identifications may require a composite overlay of several signals demonstrating co-localization and some of these techniques are currently limited to a single wavelength.
Thus, while powerful imaging instruments have been developed, these have been limited by the overlap of fluorescent emission spectra or the devices are limited to a single wavelength. There remains a need for a method and system that is able to identify co-localized parameters in a manner that is not limited by spectral overlap.